Adapted Physical Activity Quarterly, 2017, 34, 295 -310 https://doi.org/10.1123/apaq.2016-0057 © 2017 Human Kinetics, Inc.
APPLICATIONS
Nutritional Habits and Performance in Male Elite Wheelchair Basketball Players During a Precompetitive Period Amelia Ferro, Guadalupe Garrido, Jorge Villacieros, Javier Pérez, and Lena Grams Technical University of Madrid Physical condition and an optimized diet are relevant to enhance performance and recovery. The diet composition and meal frequency of eleven elite wheelchair basketball players were estimated using a 3-day food-weighing diary in two months during the precompetitive-period. Performance was determined through a 20 m sprint test. The players consumed 4.2 ± 0.8 meals/day in May and 4.5 ± 0.9 meals/day in June, resulting in total energy intakes of 2492 ± 362 kcal/d and 2470 ± 497 kcal/d, respectively. The macronutrient distribution was 3.8 ± 1.3 g/ kg carbohydrates, 1.7 ± 0.6 g/kg protein, and 36 ± 5% of energy derived from fat in May, and 4.2 ± 1.9 g/kg carbohydrates, 1.5 ± 0.5 g/kg protein and 32 ± 5% of energy derived from fat in June. The maximum velocity of the sprint test improved from 4.77 ± 0.31 m/s in May to 5.19 ± 0.23 m/s in June. Our results revealed carbohydrate intake below and fat intake above recommendations, but improvements of dietary patterns. Further nutritional advice is necessary to ensure health and performance improvements. Keywords: diet composition, nutrient timing, macronutrients, speed, kinematics
Interest in wheelchair sports has been growing over the last several years (Krempien & Barr, 2011; Rastmanesh, Taleban, Kimiagar, Mehrabi, & Salehi, 2007), and the Paralympic Games have become one of the world’s largest sporting events. Therefore, the rising competitive demands, external pressures, and the need for high-performance levels are becoming more challenging for athletes (Krempien & Barr, 2011; Rastmanesh et al., 2007). In wheelchair basketball, which is one of the most popular wheelchair sports, performance is based on three factors: the athlete, the wheelchair, and the interaction between the two (Goosey-Tolfrey, 2010). The adaptation of the wheelchair to the game has led to wheelchairs with minimized weight (Cooper & De Luigi, 2014) and to improvements in propulsion through biomechanical enhancements (Vanlandewijck, Theisen, & Daly, 2001),
The authors are with the Faculty of Physical Activity and Sports Science, Technical University of Madrid, Madrid, Spain. Please address author correspondence to Amelia Ferro at
[email protected] 295
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both of which allow for higher levels of performance. Finally, the athletes’ physical condition plays an important role, and as such, they are undertaking training programs that are comparable to those of their able-bodied counterparts (Broad & Burke, 2014). To assess starting and sprinting performance of players on the court, the 20 m sprint test is a common field test in wheelchair basketball (De Groot, Balvers, Kouwenhoven, and Janssen, 2012; Ferro, Villacieros, & Pérez-Tejero, 2016; Vanlandewijck, Daly, & Theisen, 1999; Yanci et al., 2015). In addition to physical fitness, optimal nutrition is required to achieve the goals of performance in games and high-volume training (Goosey-Tolfrey & Crosland, 2010; Krempien & Barr, 2011; Rastmanesh et al., 2007) as well as to compensate for the high energy expenditure of training (Kreider et al., 2010; Rodriguez et al., 2009; Thomas et al., 2016). An optimal dietary intake of carbohydrates maintains body weight and replenishes glycogen stores, protein builds and repairs tissue, and fat provides essential fatty acids and fat-soluble vitamins (Kreider et al., 2010; Rodriguez et al., 2009; Thomas et al., 2016). Existing recommendations from the American College of Sports Medicine (ACSM) and the International Society of Sports Nutrition (ISSN) for nutrient intake in relation to exercise intensity are based on nondisabled athletes, and no specific recommendations for Paralympic sports exist to date (Goosey-Tolfrey & Crosland, 2010; Kreider et al., 2010; Krempien & Barr, 2011; Rodriguez et al., 2009; Thomas et al., 2016). Although some differences have to be considered—such as a smaller muscle mass (Goosey-Tolfrey & Crosland, 2010), a limited sweating response (Price, 2006), and an altered maintenance of bowel function in athletes with spinal cord injuries (SCIs; Levine, Nash, Green, Shea, & Aronica, 1992)—the principles of sports nutrition can be transferred to Paralympic athletes. However, existing studies have demonstrated inadequate nutritional key points, such as low carbohydrate or high fat intake in Paralympic and wheelchair basketball athletes (Goosey-Tolfrey & Crosland, 2010; Krempien & Barr, 2011; Krempien & Barr, 2012). Because of these insufficiencies and the abovementioned differences to nondisabled athletes, meal frequency, including the intake of snacks between meals, may play an important role in reaching nutritional guidelines that has not yet been studied for wheelchair athletes. Therefore, aims of this study were to (a) describe dietary patterns before and after nutritional advice intended to reach sports nutrition recommendations during a precompetitive period in wheelchair basketball, (b) evaluate the meal frequency of the wheelchair basketball players on the Spanish men’s national team during two training camps, and (c) determine improvements of performance between the camps.
Method Participants Eleven elite male wheelchair basketball players from the Spanish national team participated in this study. The research was conducted during two high-intensity training camps in the precompetitive period between May and June in one year. None of the participants experienced injuries that had the potential to constrain their ability to perform the research task. The Ethics Committee of the Technical University of Madrid (Spain) approved the study, and it was undertaken in accordance with the Helsinki Conference for research on humans (Williams, 2008). The APAQ Vol. 34, No. 3, 2017
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volunteer participants were informed about the purpose of the study and gave their written consent before taking part in it.
Anthropometrics Height was determined to the nearest 0.1 cm using a stadiometer (DKSH Switzerland Ltd., Switzerland) in a standing position if possible, and the formula recommended by Canda (2009) was applied to estimate height based on arm span and seated height for athletes who were unable to stand. Body weight was measured to the nearest 0.1 kg with athletes wearing minimal clothing using a calibrated scale (Kern, Twister Medical, Spain).
Diet Composition Diet composition was estimated using a food-weighing diary (1 g accuracy; MettlerToledo S.A.E, Barcelona, Spain) over three consecutive days in May and again in June. The weighing of each individual food item was performed by researchers during main meals: breakfast, lunch, and dinner. All foods and energy-containing drinks consumed outside the main meals were considered as snacks. Snacks were taken from the buffet or from vending machines at the training site and were also weighed and noted as snacks. Before the next measurement, possible leftovers of the snacks were collected and weighed. Food and beverages from the vending machines, which were not free of charge, were reported, and players provided leaflets of consumed food and drinks, which consisted of cookies, prepared cakes, and isotonic drinks. All players ate together and chose their food freely from a buffet at the Higher Sport Council in Madrid (Spain); the buffet included starters, main courses, salads, fruits, deserts, and a variety of bread. As it is common for national teams to hold training camps in the precompetitive period and during championships, it seems likely that their food selection represented their normal habits for these important periods. The buffet offered the same food choices during the second evaluation. The recipes of each meal were provided by the kitchen staff, and recipes not already included in the food composition database were added. To determine supplement intake, the players reported the daily amounts taken and provided leaflets, labels, or packaging information of each supplement, which were also included in the database. DIAL v.2 software (Alce Ingeniera, Madrid, Spain) was used to determine daily nutrient intake, including the macro- and micronutrient composition. After the first period, a nutritionist provided individual written reports, including nutritional modifications with specific food intake recommendations, to optimize each player’s diet composition, based on anthropometric data, energy expenditure, and personal intentions, such as gaining or losing weight, estimated through a questionnaire before the first period. Additional individual feedback was given before the second period, and the importance of meal frequency and snacks was also emphasized. All nutritional pieces of advice applied to recommendations for able-bodied athletes because of the lack of specific recommendations for Paralympic athletes (Kreider et al., 2010; Rodriguez et al., 2009; Thomas et al., 2016). Therefore, macronutrients were expressed in grams per kilogram of body weight to give the player more practical advice: carbohydrates 5–8 g/kg, protein 1.2–2 g/ APAQ Vol. 34, No. 3, 2017
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kg, and fat 0.5–1.5 g/kg (Kreider et al., 2010; Rodriguez et al., 2009). Because the study was conducted before the updated recommendations from the ACSM were published, we used the ACSM recommendations published in 2009 for nutritional optimizations (Rodriguez et al., 2009; Thomas et al. 2016). Energy expenditure during each training camp was estimated through a 24 hr written activity protocol. Resting energy expenditure was estimated according to Abel, Platen, Rojas Vega, Schneider, and Struder (2008) to determine the energy cost of physical activities; the compendium of Collins et al. (2010) was used for athletes with spinal cord injuries; and Bernardi et al. (2010) or Abel et al. (2008) was used for other athletes, such as amputees. The estimated energy expenditure was used to compare the intensity of each training camp, both of which took place during the precompetitive period.
Sprint Test On the second day of each period, the players performed two series of 20 m sprint tests. They used their own game wheelchairs and prepared before the test as they normally would for a competition. The test started with a 15 min warmup, and between the two series, a rest of 5 min was given. The players waited at the starting line with the front wheels on the line and their trunk behind. They could independently carry out preparatory driving movements and start when they were ready. A type 1 laser sensor (LDM301, Jenoptik, Jena, Germany) integrated into a kinematic analysis system in real time for the training and the sports competitions by Ferro and Floría (2010), BioLaserSport® (Ferro, 2012), was used to measure the players’ displacement along the test. The laser beam hit the backrest of the wheelchairs at a height of 0.63 m, with the horizontality of the beam being controlled. Position data were recorded at a sampling frequency of 2000 Hz with an accuracy of ±0.06 m and a resolution of 0.001 m and were processed with a routine developed with DasyLab v.10.0 (National Instruments, Austin, TX, USA). The data were filtered at a frequency of 3 Hz, with a secondorder Butterworth low-pass filter. The maximum velocity (Vmax) and average velocity (Va) were calculated in five sections (0–3 m, 3–5 m, 5–10 m, 10–15 m, and 15–20 m) so that a more accurate assessment of the kinematic data could be obtained. The average of the two attempts was recorded. The intraclass correlation coefficients (ICC) were ≥ 0.94 for Vmax and ≥ 0.97 for Va.
Statistical Analysis Normal distribution was tested with the Shapiro-Wilk test. To establish possible differences in the distribution of meals and in the velocities of the sprint tests, analysis of variance with repeated measurements was performed with post hoc tests corrected by Bonferroni and with η2 as effect size. For comparing the two periods, May and June, paired two-sided Student t tests for parametric and Wilcoxon tests for nonparametric data were performed. Cohen’s d was determined to estimate the effect size. Fisher’s exact tests were used to test the proportion of players reaching the recommendations between the two periods. All data are given as the mean ± SD. Significance was accepted at p < .05. All tests were performed with SPSS Version 22 (IBM Corp., Armonk, NY, USA). APAQ Vol. 34, No. 3, 2017
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Results Participants Characteristics of the participants are shown in Table 1. Their body weights and body mass indexes (BMI) remained stable during the two training camps (Table 1). The intensity of the camps showed no significant difference (p > .05; Table 2).
Diet Composition Total energy intake was 34.8 ± 9.8 kcal/kg in May and 34.7 ± 12.6 kcal/kg in June (p > .05). Energy intake and distribution of macronutrients showed no significant differences for main dishes between May and June (Table 2). Six players reached the recommendations for carbohydrates in May, and nine in June (p > .05); for protein, six in May and seven in June (p > .05); and for fat, four in May and nine in June (p > .05). There was a significant difference between May and June in the energy intake of the main dishes (p < .001, η2 = .80), with lunch being the highest-energy meal in both May and June in terms of energy distribution (p < .001, η2 = .74), carbohydrate distribution (p < .001, η2 = .78), protein distribution (p = .002, η2 = .46), and fat distribution (p < .001, η2 = .72). The significances of the post hoc tests are shown in Table 2. The distribution of energy intake from lunch was significantly higher in June compared with May (p = .020, d = 0.46; Table 2). Daily water intake did not differ significantly between May (2565 ± 917 ml) and June (2640 ± 697 ml). The combined energy intake and the distribution of macronutrients of all three snacks showed no significant differences between May and June (Table 2). Macronutrient intakes in gram per kilogram of body weight for all six meals are shown in Table 3. The amount of carbohydrates consumed at breakfast was significantly higher in June than in May (p = .044, d = 0.29). Figure 1 provides the profile of fat intake and shows a significant increase of polyunsaturated fat (p = .034, d = 1.02) and a significant reduction of saturated fats (p = .045, d = 1.05), with two players under the recommended 10% in May and seven in June (p = .080). Cholesterol intake was likewise significantly reduced in June (322 ± 94 mg) compared with May (478 ± 215 mg, p = .026, d = 0.94). One player in May was under the recommended amount of 300 mg, and six were under in June (p = .063).
Meal Frequency From the six possible meals per day, the players consumed 3.8 ± 0.8 meals in May and 4.0 ± 0.8 in June, with 9 players eating all three main dishes in May and 10 in June. No player consumed three snacks per day; the average was 0.8 ± 0.8 in May and 1.0 ± 0.8 in June. In addition, the players drank only water outside the main dishes 0.5 ± 0.5 times a day in May and 0.5 ± 0.4 times in June.
Sprint Test The overall time of the 20 m sprint test was significantly higher in May (5.34 ± 0.29 s) compared with June (5.09 ± 0.26 s, p = .002, d = 0.91). Figure 2 shows the results of the sprint tests by sections, which showed significant interaction effects APAQ Vol. 34, No. 3, 2017
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—
—
—
—
—
—
—
SCI
SCI
SCI
SCI
SCI
SCI
SCI
179 ± 6
—
—
—
—
—
—
—
—
—
—
—
Body height (cm)
74.8 ± 14.9
90.6
75.0
69.0
47.0
68.0
73.5
61.9
72.0
75.0
88.5
102.0
Body weight (kg)
23.3 ± 4.0
—
—
—
—
—
—
—
—
—
—
—
BMI (kg/m2)
May
2492 ± 362
2479
2191
3127
2524
2183
2004
2939
2111
2849
2437
2564
EI (kcal)
Note. BMI = body mass index; EI = energy intake; SCI = spinal cord injury (including spina bifida).
30 ± 6
—
SCI
Mean ± SD
—
—
Amputee
Amputee
—
Amputee
Age (years)
Characteristics of the Participants
Amputee or SCI
Table 1
75.1 ± 14.5
86.4
72.0
69.0
47.5
68.0
73.5
61.9
81.5
75.7
88.5
102.0
Body weight (kg)
23.4 ± 3.9
—
—
—
—
—
—
—
—
—
—
—
BMI (kg/m2)
June
2470 ± 497
1597
2732
3446
3000
1910
2195
2424
2437
2386
2558
2486
EI (kcal)
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Energy (kcal)
835 ± 184b, c
227 ±251
2492 ± 362
3591 ± 711
Dinner
Snacks
Total
EE
Protein (%) Fat (%)
Energy (kcal)
—
45.3 ± 7.3
44.4 ± 28.1
34.9 ± 12.4b
42.2 ± 9.7a
—
—
35.5 ± 4.7
12.3 ± 14.5 22.0 ± 18.4 19.1 ± 4.8
16.7 ± 6.0a, b
Energy (%)
3791 ± 732
2470 ± 497
191 ± 165
—
—
7.3 ± 6.2
28.6 ± 7.6b, c
Protein (%)
Fat (%)
—
49.3 ± 8.2
48.1 ± 31.7
35.0 ± 12.1b
—
17.0 ± 2.8
15.3 ± 17.3
20.3 ± 6.7b
17.7 ± 3.0
—
32.1 ± 5.3
16.8 ± 12.3
42.4 ± 10.5b
35.1 ± 7.9a
66.8 ± 12.2a, b 13.4 ± 4.9b 17.2 ± 10.8a, b
CHO (%)
35.7 ± 6.4c 1144 ± 228a, c 47.3 ± 10.3a, c, * 45.5 ± 10.2a
19.9 ± 5.7 43.8 ± 8.3b, c 704 ± 230b, c
20.8 ± 4.6a
57.0 ± 13.2a, b 15.0 ± 4.9a 27.3 ± 12.4b 430 ± 187a, b
CHO (%)
June
Note. CHO = carbohydrate; Total = total energy intake, including main dishes and snacks; EE = energy expenditure. *p < .05, May vs. June. a Breakfast vs. lunch, bbreakfast vs. dinner, clunch vs. dinner, p < .05.
—
—
9.0 ± 9.6
33.5 ± 6.0b, c
1022 ± 252a, c 41.4 ± 10.1a, c, *
16.0 ± 7.5a, b
Energy (%)
Lunch
Breakfast 406 ± 208a, b
Type of meal
May
Table 2 Daily Energy Intake and Macronutrient Distribution for Main Meals and Combined Snacks and Calculated Energy Expenditure
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0.11 ± 0.12
1.53 ± 0.68
0.20 ± 0.25
1.05 ± 0.64
0.03 ± 0.06
3.76 ± 1.30
Morning snack
Lunch
Afternoon snack
Dinner
Evening snack
Total
Note. CHO = carbohydrate. *p < .05, May vs. June.
0.83 ± 0.46*
Breakfast
CHO (g/kg)
1.68 ± 0.64
0.07 ± 0.19
0.57 ± 0.20
0.05 ± 0.10
0.73 ± 0.28
0.07 ± 0.12
0.20 ± 0.11
Protein (g/kg)
May
1.39 ± 0.43
0.01 ± 0.01
0.56 ± 0.17
0.03 ± 0.05
0.56 ± 0.17
0.06 ± 0.09
0.18 ± 0.15
Fat (g/kg)
Macronutrient Intakes for All Six Meals
Type of meal
Table 3
4.24 ± 1.92
0.04 ± 0.08
0.92 ± 0.62
0.22 ± 0.25
1.91 ± 0.92
0.18 ± 0.29
0.97 ± 0.49*
CHO (g/kg)
1.48 ± 0.45
0.01 ± 0.02
0.46 ± 0.13
0.03 ± 0.05
0.69 ± 0.20
0.07 ± 0.10
0.22 ± 0.14
Protein (g/kg)
June
1.23 ± 0.41
0.01 ± 0.02
0.43 ± 0.12
0.04 ± 0.07
0.61 ± 0.20
0.02 ± 0.04
0.13 ± 0.09
Fat (g/kg)
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Figure 1 — Fat intake profiles in relation to total energy intake.
Figure 2 — Maximum velocity (Vmax) and average velocity (Va) by sections.
of periods and sections for Vmax (p < .001, η2 = .49) and for Va (p < .001, η2 = .81). The post hoc tests revealed significant differences for Vmax and Va in all sections except the first two, 0–3 m and 3–5 m, when comparing the May and June results (Vmax: 5–10 m: p = .009, d = 1.08; 10–15 m: p = .010, d = 1.12; 15–20 m: p < .001; d = 1.54, and Va: 5–10 m: p = .006, d = 0.74; 10–15 m: p < .001, d = 1.13; 15–20 m: p < .001; d = 1.52). APAQ Vol. 34, No. 3, 2017
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Discussion This study describes the meal frequency and meal composition of elite male wheelchair basketball players twice in the precompetitive phase. During the studied days in May and June, players ate 3.8 ± 0.8 and 4.0 ± 0.8 meals per day, with 82% consuming all three main meals in May and 91% in June. Only 27% of all possible snacks were eaten in May and 34% in June, which showed a tendency for an increased snack frequency but without significant differences. Together with the fact that approximately one-third of all foods and drinks consumed outside the main dishes were merely fluids, it seemed likely that the players were more aware of fluid replacement and not of the possible benefits of snacks containing carbohydrates and protein during, before, and after exercise (Kreider et al., 2010; Price, 2006). It is rather unlikely for highly organized sports teams to not consume snacks during exercise (Erdman, Tunnicliffe, Lun, & Reimer, 2013). However, keeping in mind that access to a toilet can be difficult for wheelchair users, it might be an individual strategy not to consume snacks or drinks to avoid interrupting training sessions or games. On the other hand, for athletes with SCIs gastrointestinal conditions, their digestion system may have tremendous influence on their eating habits because of longer digestion time (Lin, Kim, Hsiao, & Brown, 2002), which makes their timing of nutrition more difficult than that of able-bodied athletes. Regarding our biomechanical measurements, we observed improvements in Vmax and Va except in the starting phases (0–3 m and 3–5 m sections). This could be explained by the fact that the training between May and June focused more on tactics and technics than on strength or explosive strength training and that the energy of the first few seconds depends on adenosine triphosphate and creatine. In the 5–10 m section, the players performed at higher velocities in June than in May, with a 5% higher Vmax and a 4% higher Va. In the 10–15 m section, the values were 6% higher for both Vmax and Va, and in the 15–20 m section they were 8% higher for both Vmax and Va. Concerning nutrition in general, the distribution and contribution of the breakfast or dinner before the test day, with tests performed in the morning, could have influenced the performance of the players. Vanlandewijck et al. (1999) developed a field test battery for coaches to evaluate the wheelchair basketball skills of players, including a 20 m sprint test. They obtained an average velocity of 3.37 m/s over 20 m (Vanlandewijck et al., 1999), while the participants achieved velocities of 3.76 ± 0.20 m/s in May and 3.94 ± 0.20 m/s in June. This difference could be explained partly by the fact that the participants were elite athletes and that improvements in wheelchair design and biomechanics, together with improved training, had occurred since the study of Vanlandewijck et al. (1999). The athletes’ daily energy intake and the intensity of the training camps, which took place in the precompetitive period, did not differ. Their energy intake was higher in both May and June (2497 ± 362 kcal and 2470 ± 497 kcal, respectively) compared with other elite male wheelchair basketball and tennis players (2060 kcal; Goosey-Tolfrey & Crosland, 2010) but lower compared with elite able-bodied basketball players (4284 kcal; Bescos-Garcia & Rodriguez-Guisado, 2011). The contribution of macronutrients was at the lower limit of the carbohydrates intake (45–65%) and at the upper limit of the fat intake (20–35%), based on current recommendations (Kreider et al., 2010). The same tendency was shown by Goosey-Tolfrey and Crosland (2010) and by Krempien and Barr (2012), but other APAQ Vol. 34, No. 3, 2017
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training intensity recommendations would suggest a higher amount of carbohydrates and a lower fat intake (Kreider et al., 2010). Although there are no nutritional recommendations for disabled athletes to date, the existing recommendations for able-bodied (Kreider et al., 2010; Rodriguez et al., 2009) can be applied to disabled athletes if their impairment is taken into account. In the case of SCIs, no strong evidence exists that the muscles of these athletes responded differently than those of able-bodied athletes, and substrate oxidation rates are comparable (Knechtle, Muller, Willmann, Eser, & Knecht, 2003). However, the muscle mass of disabled athletes is smaller because of paralysis and a reduced sympathetic nervous system activity below the level of lesion, which leads to a reduced aerobic capacity (Leicht, Bishop, & Goosey-Tolfrey, 2012). Therefore, energy expenditure and requirements for athletes with SCIs are lower than those for their able-bodied counterparts (Croft, Dybrus, Lenton, & Goosey-Tolfrey, 2010). But how much lower is difficult to assess, because the calculation of energy expenditure by existing estimations—such as the compendium by Collins et al. (2010), used in this study to calculate the intensity of the training camps—could not be easily transferred to wheelchair athletes, since even the experience of wheelchair propulsion can reduce energy expenditure in trained compared with novice wheelchair users (Croft et al., 2010). To date, no recommendations for meal frequency other than before, during, and after exercise exist (Kreider et al., 2010; Rodriguez et al., 2009). Nevertheless, more meals per day seem to be a logical strategy to increase energy intake without the side effects of gastric discomfort from larger meals (Broad & Burke, 2014). Burke et al. (2003) showed a moderate correlation between eating intervals and energy intake in able-bodied male Australian endurance athletes, with an intake of 3033 ± 979 kcal divided into 5.6 ± 1.1 meals. The same eating habits with 5 meals per day were also determined in able-bodied male Canadian (3055 ± 947 kcal) and Brazilian (3678 ± 1075 kcal) athletes (Erdman et al., 2013; Nogueira & Da Costa, 2004). The eating habits of wheelchair athletes of one main meal does not seem uncommon, as other studies have discovered similar results, and only the time of day—that is, lunch or dinner—varied (Burke et al., 2003; Erdman et al., 2013; Garrido, Webster, & Chamorro, 2007; Nogueira & Da Costa, 2004). The energy intake for lunch was comparable between the participants and the Brazilian athletes, whose total energy intake was the highest of all studies analyzed (Burke et al., 2003; Erdman et al., 2013; Nogueira & Da Costa, 2004). This could be due to the buffet-style diet at training camps, which contained a great variety of food (Garrido et al., 2007). However, we believe that the participants’ eating habits during these intensive weekends were comparable to those at international competitions, so the choice of meals should be representative. In fact, during both periods, they had the possibility to choose their food freely from a buffet offering the same choices that were available at the training site. Recommendations for able-bodied athletes regarding dietary intake in relation to exercise intensity took only two macronutrients, carbohydrates and protein, into account, with daily amounts of 5–10 g/kg carbohydrates, depending on exercise intensity, relative to 1–2 g/kg protein (Kreider et al., 2010; Rodriguez et al., 2009). Regarding the lower energy expenditure in wheelchair basketball, we expected that the participants’ carbohydrates needs would be at the lower limit of the recommendations (Croft et al., 2010; Kreider et al., 2010; Rodriguez et al., 2009). This consideration was supported by Goosey-Tolfrey and Crosland (2010) APAQ Vol. 34, No. 3, 2017
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and Krempien and Barr (2012), who showed dietary intakes of 4.3 g/kg and 4.4 g/kg of carbohydrates, respectively. In addition, calculating an intake of 5 g/kg of carbohydrates, which is at the lower limit of the recommendations of the ACSM for healthy active people (Rodriguez et al., 2009), would result in 1,500 kcal for a body weight of 75 kg, leading to a high contribution of 60% carbohydrates by an assumed energy intake of 2,500 kcal. Interestingly, the athletes did not reach these smaller amounts of carbohydrates in either May (3.8 ± 1.3 g/kg) or June (4.2 ± 1.9 g/kg), except for one athlete in May and three in June, which is attributed to their high fat intake during the training camps that was at the upper limit of recommendations and could have been reduced in favor of carbohydrates. In contrast, their protein intakes in May and June were 1.7 ± 0.6 and 1.5 ± 0.5 g/kg, respectively, which were well within the recommendations. Even if the participants reached protein recommendations for optimal recovery as a group, special care should be taken for each individual because a higher intake of protein might be necessary to support and promote the healing of pressure ulcers or wounds, which are often seen in wheelchair athletes (Lee, Posthauer, Dorner, Redovian, & Maloney, 2006). In addition to the amount of carbohydrates consumed per day, the timing of consumption in relation to trainings sessions is also important, and the training sessions were held twice per day, once in the morning and once in the afternoon. In able-bodied athletes, limited glycogen stores lasted from 90 min up to 3 hr, depending on exercise intensity, so carbohydrate intake of between 1 and 4 g/kg is recommended before exercise (Kreider et al., 2010; Rodriguez et al., 2009). Our results showed a significant increase in carbohydrate intake at breakfast from May to June, from 0.8 ± 0.5–1.0 ± 0.5 g/kg, which reached the lower limit of the recommendations. On an individual level, approximately half of the players achieved 1 g/kg, but after an overnight fast, with depleted glycogen stores, particularly in the liver, and training sessions in the morning, it should be favorable for all players to reach at least the lower limit of the recommendations (Kreider et al., 2010; Rodriguez et al., 2009). Another important component to discuss is the avoidance of fatigue and hypoglycemia of more than 60 min during exercise because of low liver and muscle glycogen stores. Therefore, a 30–90 g/h carbohydrate intake during exercise is recommended (Kreider et al., 2010; Rodriguez et al., 2009; Thomas et al., 2016). Because the participants consumed only half of the possible snacks during exercise, the amount of carbohydrates was below this recommendation. Reasons could be less intensive training sessions than assumed or the strategy to avoid using the toilet during training. Finally, to recover from exercise, refueling of glycogen stores with 1–1.2 g/ kg carbohydrates is recommended between training sessions (Kreider et al., 2010; Rodriguez et al., 2009). During lunch, the participants consumed higher amounts of carbohydrates in May and in June (1.5 ± 0.7 and 1.9 ± 0.9 g/kg, respectively), with 8 athletes above the upper limit in May and 7 in June. One to 1.5 g/kg carbohydrates should be ingested to refuel after exercise (Kreider et al., 2010; Rodriguez et al., 2009). At dinner, we found a carbohydrate intake of 1.1 ± 0.6 g/kg in May and 0.9 ± 0.6 g/kg in June, with 7 athletes in both May and June below the recommendations. This amount could have easily increased with an appropriate evening snack. In fact, besides common reasons to avoid an evening snack, such as overconsumption at dinner or being exhausted and going early to bed, digestion time APAQ Vol. 34, No. 3, 2017
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differs widely among individuals with SCIs, and therefore individual solutions for disabled athletes seem essential to overcome these difficulties. Overall, the ratio between carbohydrates and fat was insufficient, with fat consumption above the recommendations. Although the composition of breakfast improved significantly, both the total amount and the distribution of fat at lunch did not change despite our written and oral feedback. A reduction of fat at lunch should have led to higher carbohydrate amounts, reaching recommendations of 5 g/kg carbohydrates (Kreider et al., 2010; Rodriguez et al., 2009). In contrast, the recommended protein intake could be reached with a normal diet without supplements, as previously shown by Goosey-Tolfrey and Crosland (2010) and Krempien and Barr (2012). One-third of the participants failed to reach the recommendations, which was comparable to the findings of Ribeiro, da Silva, de Castro, and Tirapegui (2005), who reported that 35% of wheelchair athletes had below-normal levels of the serum insulin-like growth factor-1 (IGF-1), a sensitive indicator of protein nutritional status. Our advice between the two training camps regarding the personal intentions were successful, and the two players who had an intention reached their goal to gain and lose weight, respectively. Our results revealed the limited usefulness of calculating energy expenditure of wheelchair athletes with existing estimations. The energy intake of ours athletes was greater than their energy expenditure by about 1,000 kcal/day, calculated according to Collins et al. (2010), which is probably an overestimation, since their body weights remained stable from May to June, indicating that their real energy expenditure was much closer to their energy intake than that 1,000 kcal/day gap implies. However, because we expected an overestimation, we used the compendium from Collins et al. (2010) only to compare the intensity of the training camps. Sprint measurements of nondisabled athletes by laser technology have been shown to be less accurate during the start of the sprint, because the center of mass moves in relation to the lower back (Simperingham et al., 2016). But these limitations affect only the start, and the measurement of distances over 10 m showed high validity (Simperingham et al., 2016). Together with the fact that the laser hits the backrest of the wheelchair and not the moving lower back, our measurement of the average velocity over a 20 m sprint should be accurate. Wheelchair basketball players showed a lower meal frequency than able-bodied athletes. Although their energy expenditure is lower, their low snack frequency leads to higher energy intake during main meals in relation to total energy intake. Therefore, nutritional advice for wheelchair players seems to be necessary to correct imbalances, such as carbohydrate intake below recommendations and fat intake above recommendations. As this is the first study that investigated meal frequency in wheelchair basketball athletes, our results could not be compared with other investigations, such as Burke et al., 2003; Erdman et al., 2013; Garrido et al., 2007; and Nogueira & Da Costa, 2004. Although training camps during precompetitive phases and championships are common for elite athletes, future studies should investigate meal frequency of wheelchair basketball players at home. In conclusion, the current study observed on the one hand a lower energy expenditure of wheelchair basketball players compared with their able-bodied counterparts, and on the other, a high energy intake in main meals in relation to total energy intake. Therefore the strategy to reach energy balance through higher meal frequency and lower energy intake during the main meals might APAQ Vol. 34, No. 3, 2017
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be one possible solution to enhance performance. Following sports nutrition principles for nutrient timing, particularly for carbohydrates in relation to training sessions, could improve wheelchair basketball players’ performance and their macronutrient contribution because of more balanced main dishes and more frequent snacks. The individual requirements always have to be taken into account, and longer nutritional interventions are required to correct imbalances and improve dietary habits of male wheelchair basketball players, as shown in our study. Basic knowledge about sports nutrition should be improved to ensure health and performance improvements. Nevertheless, further studies should be conducted to confirm these hypotheses. Acknowledgments To the Ministry of Economy and Competitiveness (MINECO) for the project funding through the National Plan R&D&I (DEP2012-38785); to the High Council for Sport (CSD) for their support; and to the Spanish Sports Federation for People with Physical Disabilities (FEDDF) and their wheelchair basketball players for participating in this study.
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